Reversible electroencephalogram analysis method

Abstract

In recent years, a great advancement on the electroencephalogram detection and classification feature extraction technology is obtained, various behavior activities of a person are detected from epilepsy morbidities, in a traditional mode, an electroencephalogram is used for authority brain disease studying and definite diagnosis making, and a classification data resource is used for judging human thinking activities and limb, face and eye activities at present; analysis of the electroencephalogram is more and more important in the fields. The invention provides a new electroencephalogram analysis method; and through analysis on the electroencephalogram, on the basis that the classification accuracy is guaranteed, the reversible analysis method is provided. The method can be finally used for definite diagnosis making of clinical experience, the human brain state stage can be judged, and difficulties of electroencephalogram accurate quantitative analysis are avoided; meanwhile, reverse analysis on quantitative analysis results can be carried out, verification with the clinical medicine experience is finally achieved, and more scientific conclusions are obtained

Description

technical field [0001] The invention relates to the technical field of biomedical digital signal processing, pattern extraction and pattern classification, and in particular to a method for reversible analysis and processing of electroencephalogram signals that can effectively extract certain state characteristics of electroencephalogram signals. Background technique [0002] For many brain diseases, before, during and after the onset of the onset, the EEG signal changes to varying degrees. At the same time, many application classifications applied to the brain-computer interface and sleep state also mainly focus on the EEG signal. Analysis of the changing characteristics. [0003] In recent years, the detection and classification feature extraction technology of EEG signals has made great progress, from the detection of epilepsy to various human behaviors, from the traditional use of EEG signals as the authoritative research and diagnosis of brain diseases, to now through i...

AI Technical Summary

Problems solved by technology

[0009] The human brain is a time-varying nonlinear dynamical system, which is characterized by certainty in chaos. Since the EEG signal will introduce random errors after measurement, it will cause interference to the original signal; traditional signal processing techniques are often aimed at linearity, For non-time-varying problems, with the continuous development of nonlinear EEG signal processing technology, more and more nonlinear time-varying signals are processed, but the algorithm reversible analysis process is often ignored

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